The identification of novel cancer biomarkers opens the possibility for early detection, better monitoring of tumor progression, and even targeted therapy. Such markers are especially needed for ovarian cancer, which is often at an advanced stage at the time of diagnosis, leaving patients with poor prospects for survival (Mill, et al., J. Nat'l Cancer Inst. 93:1437–39 (2001); Daly, et al., Cancer Cell 1:111–2 (2002)).
Classical approaches to cancer biomarker identification involved immunizing animals with tumor cells and then screening for antibodies that recognize a cell-specific antigen (Bast, et al., N. Engl. J. Med. 309:883–73 (1983)). Recently, tumor mRNA has been compared with normal tissue mRNA in an attempt to identify up-regulated genes in cancer tissue using cDNA micro-arrays (Mok, et al, J. Nat'l Cancer Inst. 93:1458–64.3 (2001); Kim, et al., J. Am. Med. Assoc. 289:1671–804–5 (2002)). A limitation of the traditional approach is its high cost and labor intensity, while a limitation of the cDNA micro-array approach is that transcriptional activity in the tumor does not necessarily reflect the proteins observed peripherally.
Since protein-protein interactions and post-translational modifications (e.g. phosphorylation, glycosylation, and enzymatic cleavage) may alter the protein patterns found in a patient's circulation, proteomic high throughput approaches that allow for the identification of circulating biomarkers could accelerate oncology research. In this regard, there has been considerable interest in analyzing surface enhanced laser desorption/ionizaton mass spectrometry (SELDI-MS) spectra for markers useful for disease detection (Petricoin, et al., Lancet 359:572–77 (2002); Vlahou, et al., Am. J. Pathol. 1;158:1491–02 (2001)). If these approaches lead to a biomarker that can be used to detect ovarian cancer in its early stages, e.g., a test analogous to the Pap smear used for uterine cancer, survival rates could undoubtedly be substantially improved.